View the step-by-step solution to:

# Student Name - ID # XXXXXX FINAL PROJECT: PROJECT D SALARY SURVEY AFTER MBA INTRODUCTION Students pursuing MBA degrees consider several factors when...

Hello Meenaksi.angra,

Thanks for updating my answer but I didn't see the executive summary of the project or the conclusion as shown in the examples.
Student Name – ID # XXXXXX F INAL P ROJECT : P ROJECT D S ALARY S URVEY AFTER MBA I NTRODUCTION Students pursuing MBA degrees consider several factors when choosing a school. These factors can include Cost of tuition, the likelihood of landing a job within six months How much personal debt will be carried What kind of salary to expect Whether a private institution is worth the extra cost in exchange, presumably, for a higher salary. O BJECTIVE AND M ETHODOLOGY A survey of the top 38 business schools was conducted, providing a data set that addresses the concerns listed above. In addition, data related to additional costs and fees and region were included. This analysis will review these concerns in an attempt to provide some guidance to the future MBA candidate. We will use statistical analyses to evaluate the data in total by performing an exploratory data analysis on the data to identify patterns in the data. If the findings suggest it, further analysis will be performed: multiple regression analysis, testing dependent variables. G ENERAL O BSERVATIONS – A LL S CHOOLS The following data were used in the estimates to determine if the total population information could give the student any guidance. But first, the average indebtedness for M.I.T. was estimated using a simple regression on the data. Estimating to a 95% confidence level by comparing M.I.T.’s cost to other private, eastern region schools, we use the value \$63,693 for the average indebtedness. (See Appendix 1) Salary/Bonus Annual Cost Average Indebtedness Employment Rate within 6 months Mean \$ 108,109 \$ 28,812 \$ 47,888 82.78% Median \$ 106,644 \$ 34,196 \$ 48,780 82.90% Standard Deviation \$ 15,067 \$ 13,048 \$ 24,352 6.69% We first look at the Salary/Bonus distribution and compare it to Employment Rate and Annual Cost. We can say that half of the expected salaries fall between \$96,559 and \$120,408 while the Employment Rate is between 78.3% and 87.9% and the Annual cost is between \$17,500 and \$41,190 for the second and third quartiles. These charts indicated a distribution that is left skewed, meaning there are some schools with significantly lower expected values. But looking at Average Indebtedness, we see a range of the second and third quartiles between \$22,434 and \$69,458 with a right skewed distribution meaning that some students can expect considerably higher indebtedness based on the chosen school.
G ENERAL O BSERVATIONS – P UBLIC VS . P RIVATE We took another look at the population data, this time comparing the outcomes of public vs. private schools. What can the MBA candidate expect in terms of salary, costs, indebtedness, etc. if he or she attend a private school or a public school? See Appendix 3 for the outcomes of this query. We start to see some differences between public and private schools especially in salaries, annual costs and average indebtedness. C OMPARING S ALARY E XPECTATIONS TO OTHER VARIABLES Next, we want to see if there is a relationship between expected salaries and other variables. Appendix 4 contains scatter diagrams comparing salaries to Annual Cost, Average Indebtedness and the Rate of Employment. In terms of cost and indebtedness we see a general trend of increased salary as costs or indebtedness increase. Running simple regression analysis on these data give us the following: For Salary to Annual Cost, the slope is Y = 81699.70 + 0.9166(X) meaning that for every dollar increase in cost, we can see about 92 cents increase in salary. The Adjusted R Square value is 0.61275, which means that about 61.3% of increase in salary can be explained this way. (We use Adjusted R Square because of the overall number of variables in our data.) Regression Analysis - Salaries to Cost Regression Statistics Multiple R 0.793742223 R Square 0.630026716 Adjusted R Square 0.61974968 Standard Error 9291.226576 Observations 38 Coefficients Intercept 81699.70025 Annual Cost 0.916601109 For Salary to Average Indebtedness, the slope is Y = 86265.49 + 0.45613(X) meaning that for every dollar increase in cost, we can see about 46 cents increase in salary. The Adjusted R Square value is 0.5308, which means that about 53.1% of increase in salary can be explained this way. Regression Analysis - Salary to Indebtedness Regression Statistics Multiple R 0.737210858 R Square 0.543479849 Adjusted R Square 0.530798734 Standard Error 10320.90652 Observations 38 Coefficients Intercept 86265.48565 Average Indebtedness 0.456132842
Show entire document

Hi Dear, I have updated the... View the full answer

INTRODUCTION
Statistics has come to play an important role in almost every field of life and human activity. There is hardly any field where statistical data or statistical methods are used for one...

### Why Join Course Hero?

Course Hero has all the homework and study help you need to succeed! We’ve got course-specific notes, study guides, and practice tests along with expert tutors.

### -

Educational Resources
• ### -

Study Documents

Find the best study resources around, tagged to your specific courses. Share your own to gain free Course Hero access.

Browse Documents